Departamento de Engenharia Civil e Arquitectura
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[Departamento extinto em 05 de Dezembro de 2025]
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Percorrer Departamento de Engenharia Civil e Arquitectura por Domínios Científicos e Tecnológicos (FOS) "Engenharia e Tecnologia"
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- A GIS-Based Approach to Fostering Sustainable Mobility and Combating Social Isolation for the Rural ElderlyPublication . Branco, Luís; Santos, BerthaThe growing demographic trend of an aging population, particularly in remote rural areas, exacerbates social isolation and limits access to essential goods and services. This vulnerability highlights a pressing need to develop sustainable solutions for their mobility and support. Using Geographic Information Systems (GISs) and network analysis, a workflow was developed to optimize road-based transport for the elderly. The analysis utilized an electric vehicle, with its range limitations, influenced by road slopes, being a critical variable for assessing route efficiency. Two potential solutions were investigated: (1) the delivery of goods and medicines and (2) the transport of passengers and medicines. The methodology was tested using the Municipality of Seia, Portugal, as a case study, with a defined weekly visit frequency. The results demonstrate that both proposed solutions are technically viable for implementation, with the transport of passengers and medicines being the most effective option. This study provides a foundational framework for developing practical, demand-oriented, sustainable transport and logistics services to support isolated elderly populations.
- Automated Geographic Information System Multi-Criteria Decision Tool to Assess Urban Road Suitability for ActiveMobilityPublication . Santos, Bertha; Ferreira, Sandro Alfaro ; Lucena, Pollyana;The planning of greener, more accessible, and safer cities is the focus of several strategies that aim to improve the population’s quality of life. This concern for the environment and the population’s quality of life has led to the implementation of active mobility policies. The effectiveness of the mobility solutions that are sought heavily depends on the identification of the main factors that favor their use, as well as how adequate urban spaces are in minimizing existing difficulties. This study presents an automated geographic information system (GIS) decision support tool that allows the identification of the level of suitability of urban transportation networks for the use of active modes. The tool is based on the determination of a set of mobility indices: walkability, bikeability, e-bikeability, and active mobility (a combination of walking and cycling suitability). The indices are obtained through a spatial multi-criteria analysis that considers the geometric features of roads, population density, and the location and attractiveness of the city’s main trip-generation points. The treatment, representation, and study of the variables considered in the analysis are carried out with the aid of geoprocessing, using the spatial and network analysis tools available in the GIS. The Model Builder functionality available in ArcGIS® was used to automate the various processes required to calculate walking, cycling, and e-biking travel times, as well as the mobility indices. The developed tool was tested and validated through its application to a case study involving the road network of the urban perimeter of the medium-sized city of Covilhã, Portugal. However, the tool is designed to be applied with minimal adaptation to different scenarios and levels of known input information, providing average or typical values when specific information is not available. As a result, a flexible and automated GIS-based tool was obtained to support urban space and mobility managers in the implementation of efficient measures compatible with each city’s scenario.
- Evaluation of Pedestrian Crossing Accidents Using Artificial Neural NetworkPublication . Santos, Bertha; Gonçalves, Jorge; Amin, Shohel ; Vieira, Sandra Cristina Gil ; Lopes, Carlos Manuel Valença MartinsMost of European cities face increasing problems caused by excessive traffic of conventional fuel-based transport modes. To reverse this situation, sustainable urban mobility policies have been promoting soft modes of transport, such as walking. Despite the advantages of walking in reducing traffic congestion and pollution, cities have not always evolved to accommodate the needs of pedestrians. According to the European Commission, in 2020, 20% of road fatalities in the European Union (EU) and 21% in Portugal were pedestrian. Pedestrian fatality rates per million population was 9.7 for all EU countries and 13.1 for Portugal. In European and Portuguese urban areas, 36% and 27% of the fatalities were pedestrians’ and 49% and 56% of all pedestrian fatalities were elderly’s (respectively). In pedestrian infrastructures, crossings are considered the most critical element due to conflicts between vehicles and pedestrians. It is then essential to identify and minimize risk factors that increase the probability of accidents in these locations. The proposed work intends to assess this challenge by using Artificial Neural Network (ANN) to create pedestrian severity prediction models and identify road and pedestrian risk factors for accident occurred in or near urban crossings. The official Portuguese database on run over pedestrian accidents occurred between 2017–2021 was analyzed with ANN considering two scenarios: pre-Covid-19 and during Covid-19 period. Results obtained demonstrate that the use of ANN can promote a proactive infrastructure management, suggesting that crossings traffic lights operation, lighting, shoulders and pavement conditions, high speed limits (51–90 km/h) and pedestrians moving in soft modes are critical factors.